Even we notice or not the algorithms are everywhere in our daily life. When we are making payment with credit card, while we are searching something at the search engine or while our smartphone camera automatically finds the faces at the camera and focusing on them, The algorithms are working in the background and making our lives easier.

We tend to think algorithms came into our lives by the computer age but it is wrong. Algorithms are helping us from the ancient times. For example, Euclid’s algorithm to find the greatest common divisor, which we learn at primary school math classes, probably one the oldest algorithm.

Algorithms are for solving the problem in structural, efficient and fastest way. So let’s look at some algorithms which make our lives easier.

PageRank Algorithm

One of the well-known algorithm of modern time is PageRank algorithm. It is a ranking algorithm and when you enter a query, it is sorting search results that you most likely interested in, based on ranking scores.

Matching Algorithms

Online dating is so popular at these days. Even studies show that over third of marriages started online. These dating websites are using matching algorithms. They are searching through your profiles and match people up based on their likes, dislikes, and personality. Another research also shows couples who met online tend to be happier and have longer marriages.

Shortest Path Algorithm

The salesman must visit all cities in the shortest way. But how to do it? The first solution comes to our mind is brute force solution of this problem – trying all possible routes and then decide which one is the shortest.

But unfortunately when the number of cities increased possible routes are also increasing exponentially. When we look at the numbers we will see better:

Machine Learning Algorithms

Now, we came into another breakpoint at technology. By using past data and computational power, computers can learn like us. We don’t need to program them explicitly. If we feed them with enough and appropriate data; they can find patterns in and they can learn from data.

Programs don’t have frozen mind anymore. They can learn and adapt themselves. We must be ready for the more automated world. Algorithms will shape our lives more and more in the future.

Job Interviews are always scary. Most of the time we take negative results close to our heart and take it personally. But it is not like this. First of all we must change our mind. Then interviews will not be scary, instead they will be free lesson for us.

Just a simple mindset shift can change our life fully. If you start to believe that we can improve our talents and abilities by working on them, you will realise every failure will push you to learn more, every unsuccessful attempt will show you where you need to correct for next time.

https://www.smore.com/n3eyx-growth-mindset-resources

2. Ask Good Questions

Interview is not an exam for you. Also, it is our chance to ask questions to interviewer to understand about the job, about the company. Don’t forget; main purpose is our happiness at our new job and its benefits. So we must be sure and convinced that this job is fitting to us. Don’t worry it is interviewer responsibility to take care for the company.

You must prepare some question list for you before the interview and don’t forget it is as important as being ready for technical questions. If you don’t know what you really want for yourself or what is good for yourself who will care about this?

https://www.linkedin.com/pulse/good-question-brett-goffin/

3. Don’t Lie

We can think interviews are the process of selling yourself. So don’t lie for the short term success. You must take care about your personal brand. For example if you lie about your abilities you are not only deceiving your interviewer, but you are also running away from facing up with the problem.

https://medium.com/@lisamloeffler/dont-lie-c21fd51fb608

Yes, job interviews are scary, difficult, very open to surprise with unpredictable questions but it is just an interview. It is just a door to your next job.

But it is not the last door you can knock. Even if you failure at this one, keep going. Your next job and bright future is waiting you ahead. Just keep walking.

This study aims to define the energy usage efficiency in apple cultivation in the Province of Tekirdağ. The study was conducted during 2015 production season through observation and measurement in an apple garden with a land area of 12 da and located in Nusratlı village in Central Tekirdağ. It has been tried to reveal the role of mechanization energy among all the inputs. According to the calculated data, in apple cultivation the respective figures for total energy input, total fruition, total energy output, energy output/input rate, specific energy, energy productivity and net energy have been calculated as 58839.65 MJ ha-1, 38370 kg ha-1, 92088.00 MJ ha-1, 1.56, 1.53 MJ kg-1, 0.65 kg MJ-1 and 33248.35 MJ ha-1 respectively. As a result, among the general energy inputs in apple cultivation, the highest energy consuming items have been respectively defined as fertilizer energy, fuel-oil energy, chemicals, machinery, human labour and irrigation energy.

Yes, it is very easy to see popularity of data science increasing like a rocket

Data Science Trend over years

But just this graph is not only explaining the whole story. Because when we look at top 5 related queries we saw a different face of the story.

Data Science Top Five Queries

It is very obvious there is a strong interest on data science but as we see on the queries “what is data science” is at 2nd and “what is data” is in 4th place of the query list. Actually this is really great thing because data science is very important for everyone while the world is becoming more digital (E.g. agriculture)

The question is how will we make this transformation? How we will educate people about data science? By classical education? By online course? By bootcamps? or maybe digital revolution will lead us to more effective hybrid solutions?

Smallholder family farming is the backbone of agriculture at developing countries. There are 500 millions smallholder farmer all around the world. Pests and plant diseases are one of the biggest problem of farmers and these smallholders players usually don’t have enough chance to have consultancy. Luckily machine learning can help them about this. The app Plantix can be answer of this question. Just a simple smartphone can help you detect disease by taking photo of the plant. App. is not only detecting but also suggesting you possible solutions. Every new image is increasing recognition performance.

A spraying machine was designed with this study. This machine can contuniously sets the amount of liquid chemical continuously depending on changes in leaf density, volume of the canopy, size and shapes which differs during growing season. These processes will optimise efficiency of spraying application. Ultrasonic sensors were used with this aim to define size of plant for adapting of chemical dosage octopus spraying machine was used at study. A system was designed for every arm’s of octopus machine. Three solenoid valve, one ultrasonic sensor, and electronic control unit which process and interpret the range data of ultrasonic sensor and also control solenoid valve, were added to arms. Flow rate of chemical can be set to three different value. Because every single electrovalve control different type of nozzle. Amounts of spraying chemical is set real-time by system depending on canopy volume and leaf density.